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Depth-independent segmentation of macroscopic three-dimensional objects encoded in single perspectives of digital holograms
McElhinney, Conor P.; McDonald, John; Castro, Albertina; Frauel, Yann; Javidi, Bahram; Naughton, Thomas J.
We present a technique for performing segmentation of macroscopic three-dimensional objects recorded using in-line digital holography. We numerically reconstruct a single perspective of each object at a range of depths. At each point in the digital wavefront we calculate variance about a neighborhood. The maximum variance at each point over all depths is thresholded to classify it as an object pixel or a background pixel. Segmentation results for objects of low and high contrast are presented.
Keyword(s): Depth-independent segmentation; macroscopic three-dimensional objects; single perspectives; digital holograms
Publication Date:
2007
Type: Journal article
Peer-Reviewed: Yes
Institution: Maynooth University
Funder(s): Science Foundation Ireland; Enterprise Ireland
Citation(s): McElhinney, Conor P. and McDonald, John and Castro, Albertina and Frauel, Yann and Javidi, Bahram and Naughton, Thomas J. (2007) Depth-independent segmentation of macroscopic three-dimensional objects encoded in single perspectives of digital holograms. Optics Letters, 32 (10). pp. 1229-1231. ISSN 0146-9592
Publisher(s): Optical Society of America
File Format(s): other
Related Link(s): http://mural.maynoothuniversity.ie/8281/1/JM-Depth-2007.pdf
First Indexed: 2020-04-02 06:31:22 Last Updated: 2020-04-02 06:31:22